"How to View console.log Output in Chrome" matching MCP tools:

• listMetricDefinitions

  Cortex

  List all available engineering metric definitions. USAGE - Call this endpoint BEFORE querying metrics (queryPointInTimeMetrics): 1. Once at start: Call with view='basic' to discover all available metrics - cache this response 2. Once per metric: Call with view='full' and key=METRIC_KEY to get detailed metadata - cache each response 3. Use cached metadata to construct valid point-in-time queries Cache responses in your context. Only refresh if no longer in your context window or explicitly requested (ex to check if metric readiness has changed). Query parameters: - view: 'basic' (default) returns minimal info, 'full' includes sources and query metadata - key: Filter metrics by key (supports multiple values and comma-separated lists) Full view provides query construction metadata: - supportedAggregations: Valid aggregation methods for the metric - orderByAttribute: Attribute path for sorting by metric values - groupByOptions[].key: Valid groupBy keys (use exact values, do NOT guess) - filterOptions[].key: Valid filter keys (use exact values, do NOT guess) Valid orderBy attributes for metric queries: - orderByAttribute: The metric value itself (returned in full view) - Source attributes: Any attribute from the metric's source (e.g., "source_name.attribute_name") - Dimension attributes: Any attribute from related dimensions (e.g., "source_name.dimension_name.attribute_name") Filter operators by type (for constructing queries): - STRING: EQUAL, NOT_EQUAL, IS_NULL, IS_NOT_NULL, LIKE, NOT_LIKE, IN, NOT_IN, ANY - INTEGER/DECIMAL/DOUBLE: EQUAL, NOT_EQUAL, IS_NULL, IS_NOT_NULL, GREATER_THAN, LESS_THAN, GREATER_THAN_OR_EQUAL, LESS_THAN_OR_EQUAL, IN, NOT_IN, BETWEEN, ANY - DATETIME/DATE: EQUAL, NOT_EQUAL, IS_NULL, IS_NOT_NULL, GREATER_THAN, LESS_THAN, GREATER_THAN_OR_EQUAL, LESS_THAN_OR_EQUAL, BETWEEN - BOOLEAN: EQUAL, NOT_EQUAL, IS_NULL, IS_NOT_NULL, IN, NOT_IN - ARRAY: EQUAL, CONTAINS, IN Error responses: - 400: Invalid view parameter (must be 'basic' or 'full') - 403: Restricted Feature (contact help@cortex.io)

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• get_sc_theory

  SCModeling

  Reference guide to supply-chain simulation concepts: ordering policies, BOM, FDD formulas, event-driven simulation. Pure static text — no engine call, deterministic output. Use this when the user asks a conceptual 'how does this work' question rather than asking for a number.

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• get_model_chart

  quantifyme

  Visualize a trained model's backtest — a cumulative-return chart + trade log + stats. Use after `one_shot` / `list_models` with the model's `stem` to SHOW the user how it traded (the "is it actually any good" view). In ChatGPT this renders an interactive widget. In Claude, render an interactive **artifact** from this tool's structured output: a line chart of the cumulative return plus a table of the trades. Args: stem: The model stem (e.g. "14_EURUSD_15min_Model_24") from `list_models` / `one_shot`. Returns: dict with: ok, stem, symbol, timeframe, stats {ret, wr, pf, n, mdd, sharpe}, and trades [{type, entry_time, exit_time, entry_price, exit_price, pnl, pnl_pct, exit_reason, period}] (most recent ~200). exit_reason is one of TP / SL / close_only / signal / end. ret/mdd/wr are fractions; pnl_pct is percent.

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• get_signal

  GammaRips Options Intelligence

  Deep dive on a single ticker/contract. Two `view`s: * view="detail" (DEFAULT) — the full enriched signal for one ticker: thesis, catalyst, the recommended contract, and point-in-time features (leakage-safe view). `full=true` includes the long narrative (news_summary, flow_intent_reasoning). If the ticker isn't in the pool for the date, the error lists the dates on which it does appear. * view="earnings" — the doctrine earnings-window check (RM-003): the next scheduled earnings date and whether it lands ON OR BEFORE the contract expiration (`earnings_in_window`). The engine applies this rail only at its own pick time, NOT in the pool, so pool rows CAN carry earnings-window names — check every candidate yourself. Pass the pool's `recommended_contract` and both ticker and expiration are derived. FAIL-CLOSED: unknown date -> earnings_in_window=null, treat as in-window. Args: ticker: underlying symbol (required for detail; optional for earnings if `contract` is given). view: "detail" (default) | "earnings". scan_date: detail only — YYYY-MM-DD (default: latest for the ticker). full: detail only — include the long narrative fields. expiration: earnings only — option expiration YYYY-MM-DD to test. contract: earnings only — OCC ticker supplying ticker+expiration.

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• render_spintax

  spintax.net MCP server

  Renders up to 20 variants. With a seed the output is deterministic (variant i uses seed "<seed>#<i>"); without one it is random. The engine is lenient: structural mistakes never throw, they surface in the output — run validate_spintax first.

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• brain_list_canonical_identities

  personalbrain-mcp

  Return canonical (tool_id, mcp_name, …) for every tool the wheel exposes. The authoritative source for any client (Studio, agents, FE) that needs to know how this MCP identifies its tools. Reconcile uses this output to UUID-join against the stored pricing model — no name-based UUID derivation, no guessing. Includes both ToolIdentity-seeded tools and any UUID recorded by ``@paid_tool`` that is missing from the registry. The latter appear with ``registered: false`` (and in the top-level ``unregistered`` array) so Reconcile can flag deploy drift instead of silently reporting clean when a live tool was never seeded (#174). If the operator renames a function or rebrands a slug, the mcp_name in this output changes but tool_id stays. That's the whole point of the canonical-UUID design. Also diffs the live FastMCP wire surface against the registry. Tools exposed on the wire but absent from the registry appear in ``unregistered`` so Reconcile can flag deploy drift instead of silently under-reporting (issue #175). Free, no side effects.

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• upload_asset

  SlideForge

  Upload assets for PowerPoint (.pptx) generation: company template, logo, image, or document — or AI-generate an image. Purposes: • logo — company logo for chrome (PNG/JPG/SVG, max 5MB) → logo_id • image — image for the Image component (max 10MB) → asset_id • theme — company template PPTX → theme_id; slides with it render NATIVELY on the template (masters/layouts/chrome) • generate_image — AI-generate via `prompt` → asset_id ($0.05) • translate — PPTX to translate → deck job_id ($0.02/slide; requires `target_language`) • pdf — PDF → editable slides; pass `target_language` to also translate • recreate — image OF a slide → editable PPTX slide ($0.10; honest annotate/preserve fallback, refusals free). Use `image` to just place a picture Files >3MB (pdf/translate/theme) — and recreate on chat hosts — omit `data`: a drop-zone appears in the result card; bytes never pass through the agent.

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• chrome_read_tab

  local-mcp

  Reads the rendered text content of a Google Chrome tab. Call with NO arguments to read the current (active) tab — the same tab chrome_wait_for/chrome_click/chrome_navigate just operated on; use this right after chrome_wait_for, since the tab may have navigated and its URL changed. Or identify a specific tab by `url_match` (substring match against URL; first hit wins — falls back to the active tab if nothing matches) or by `window_index` + `tab_index` (from chrome_list_tabs). Text is capped at `max_bytes` (default 100 KB). Pass `include_html: true` to also get the raw HTML source. Pass `include_links: true` to extract all links with their href and text. Requires 'Allow JavaScript from Apple Events' (Chrome → View → Developer); run chrome_setup_check if reads come back empty.

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• get_pool

  GammaRips Options Intelligence

  The GammaRips candidate pool for a scan date. One tool, four `view`s: * view="enriched" (DEFAULT) — the curated AI-enriched pool: news, technicals, catalyst, a delta-targeted recommended contract, and the 60-day momentum feature `mom_60`. Enrichment gate: overnight_score>=4 AND directional UOA>$500K, edge-ranked to the top ~50 BULLISH names. This is the daily candidate set your agent reasons over to its OWN contract (see get_playbook("run-your-own-tournament")). Served from a leakage-safe view (forward-outcome columns physically stripped); `summary=True` gives ~21 decision columns, `fields=[...]` a strict projection, `summary=False` full rows, `offset` pages. * view="raw" — the wide pre-curation overnight scan (where unusual options activity concentrated across the whole universe, BEFORE curation). Honors `direction`, `min_score`, `ticker`, `limit`. * view="features" — point-in-time FEATURE VECTORS from the leakage-safe allowlist view `enriched_features_v1` (identity + features + cohort metadata only; no outcome/label/telemetry column can appear). The quantitative substrate for joining against query_outcomes. Lags the live pool by ~1-2 trading days. * view="preview" — a minimal public teaser (ticker, direction, score, headline, directional UOA) for the most recent scan; no contract specifics or thesis. TIER: view="preview" is FREE (no key). The enriched / raw / features views are the paid product — they require an active pro subscription key; an anon call to them returns `subscription_required` (get_pool(view='preview') is named as the free entry point). Liquidity caveat (all views): `recommended_oi`/`recommended_volume` are scan-time snapshots, not live values; `recommended_spread_pct` is permanently NULL on the current data plan — re-check with get_liquidity. Args: view: "enriched" (default) | "raw" | "features" | "preview". scan_date: YYYY-MM-DD (default: latest available scan for the view). direction: "bull"/"bear" prefix filter (enriched / raw). ticker: exact ticker filter (enriched / raw / features). min_score: overnight_score floor (raw view only; clamped 0-10). limit: max rows (enriched/raw clamp 1-50, features 1-100, preview 1-20). summary: enriched only — True=compact columns, False=full rows. fields: enriched only — explicit strict column projection. offset: enriched only — pagination offset.

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• excalibur_list_canonical_identities

  excalibur-mcp

  Return canonical (tool_id, mcp_name, …) for every tool the wheel exposes. The authoritative source for any client (Studio, agents, FE) that needs to know how this MCP identifies its tools. Reconcile uses this output to UUID-join against the stored pricing model — no name-based UUID derivation, no guessing. Includes both ToolIdentity-seeded tools and any UUID recorded by ``@paid_tool`` that is missing from the registry. The latter appear with ``registered: false`` (and in the top-level ``unregistered`` array) so Reconcile can flag deploy drift instead of silently reporting clean when a live tool was never seeded (#174). If the operator renames a function or rebrands a slug, the mcp_name in this output changes but tool_id stays. That's the whole point of the canonical-UUID design. Also diffs the live FastMCP wire surface against the registry. Tools exposed on the wire but absent from the registry appear in ``unregistered`` so Reconcile can flag deploy drift instead of silently under-reporting (issue #175). Free, no side effects.

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• schwab_list_canonical_identities

  schwab-mcp

  Return canonical (tool_id, mcp_name, …) for every tool the wheel exposes. The authoritative source for any client (Studio, agents, FE) that needs to know how this MCP identifies its tools. Reconcile uses this output to UUID-join against the stored pricing model — no name-based UUID derivation, no guessing. Includes both ToolIdentity-seeded tools and any UUID recorded by ``@paid_tool`` that is missing from the registry. The latter appear with ``registered: false`` (and in the top-level ``unregistered`` array) so Reconcile can flag deploy drift instead of silently reporting clean when a live tool was never seeded (#174). If the operator renames a function or rebrands a slug, the mcp_name in this output changes but tool_id stays. That's the whole point of the canonical-UUID design. Also diffs the live FastMCP wire surface against the registry. Tools exposed on the wire but absent from the registry appear in ``unregistered`` so Reconcile can flag deploy drift instead of silently under-reporting (issue #175). Free, no side effects.

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• axint.schema.compile

  Axint

  Compile a minimal JSON schema directly to Swift, bypassing the TypeScript DSL entirely. Supports intents, views, components, widgets, and full apps via the 'type' parameter. Uses ~20 input tokens vs hundreds for TypeScript — ideal for LLM agents optimizing token budgets. Use: use for token-light JSON-to-Swift generation; use compile for full TypeScript DSL control and scaffold for TS starters. Inputs: schema kind selects intent, view, widget, or app output; options add companion metadata. Effects: read-only Swift generation; writes no files and uses no network.

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• papers.list

  Urantia Papers

  List all 197 papers in the Urantia Book with their metadata (id, title, partId, labels). Use toc.get for a hierarchical view instead.

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• execute

  mcp

  Runs JavaScript code to interact with the Mux API. You are a skilled TypeScript programmer writing code to interface with the service. Define an async function named "run" that takes a single parameter of an initialized SDK client and it will be run. For example: ``` async function run(client) { const asset = await client.video.assets.create({ inputs: [{ url: 'https://storage.googleapis.com/muxdemofiles/mux-video-intro.mp4' }], playback_policies: ['public'] }); console.log(asset.id); } ``` You will be returned anything that your function returns, plus the results of any console.log statements. Do not add try-catch blocks for single API calls. The tool will handle errors for you. Do not add comments unless necessary for generating better code. Code will run in a container, and cannot interact with the network outside of the given SDK client. Variables will not persist between calls, so make sure to return or log any data you might need later. Remember that you are writing TypeScript code, so you need to be careful with your types. Always type dynamic key-value stores explicitly as Record<string, YourValueType> instead of {}.

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• try_demo

  MCPSpend

  Run this WITHOUT an API key to see what MCPSpend output looks like. Returns a synthetic cost snapshot identical in shape to get_today_cost + list_top_tools + get_usage_this_month. Use this to preview the product before signing up.

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• get_activity_metrics

  wallet-tracker

  How many trades happened and how much value moved over a window of up to 24 hours, plus how many distinct wallets were involved. Use for how busy the market or a single token is, rather than for the individual trades. blockchain: solana, bnb, base, eth or rh wallet_type: kol, smart or whale (default kol) hours: window in hours, at most 24 (default 1) mint: restrict to one token

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• job_alert_unsubscribe_all

  FoundRole — AI Job Search & Application Tracker MCP for Claude & ChatGPT

  Unsubscribes the authenticated user from ALL of their job alerts at once, across every subscription source (regular, company page, MCP). **Input:** - `confirm`: Must be `true` to execute. The call is rejected when omitted or not true — this guards against an unintended bulk unsubscribe. **Output:** Confirms how many alerts were unsubscribed. Idempotent: returns success even when the user has no active alerts.

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• query_outcomes

  GammaRips Options Intelligence

  The realized-outcome + receipts substrate behind the engine. One tool, nine `view`s. Whole-pool composites under any FIXED exit are NEGATIVE by construction — these are a research surface (how outcomes distribute across features and exits), never a strategy track record. * view="labels" (DEFAULT) — row-level realized bracket LABELS joined to point-in-time features. horizon "same_day" (live V7.1 GIGO +40/-30) or "3d" (legacy +80/-60) — never pooled. NULL-label and illiquid rows excluded (counts in meta). `aggregate_only=True` returns summary stats instead of rows. Filters: scan_date_from/to, ticker, delta_min/max, min_overnight_score, exit_reason. * view="summary" — grouped aggregates over the labeled pool. `group_by` one of none|delta_bucket|overnight_score|premium_score|exit_reason| day_of_week|moneyness_bucket. * view="surface" — the OPPORTUNITY SURFACE: per-contract realized MFE/MAE excursions with NO exit applied (profit potential, exit free). Uses scan_date OR a `days` lookback, `ticker`, `delta_min/max`, `include_open`. `aggregate_only=True` returns MFE/MAE quantiles over the FULL filtered set — use it for exit design. The row mode is capped at 200 and truncates oldest-first WITHIN a scan_date, so its oldest date is a highest-MFE-only slice; it reports `truncated`, `matched_rows`, and `partial_scan_date` so you can see that happen. * view="harvest" — the touch-probability curve: P(premium touched +X%) with CIs, day-of-peak buckets, stop-touch rates. `targets`, `stops`, date range, delta band. * view="exit_rule" — RESEARCH-ONLY "bring your exit, we score it": rule="bracket" (target_pct/stop_pct) or rule="trailing" (trail_pct, activation_pct) scored against the surface / minute tape. * view="signal_performance" — UNDERLYING-STOCK direction outcomes for the broad pool (NOT option PnL). Filters scan_date, ticker, direction, outcome. * view="win_rate" — aggregate UNDERLYING-direction win rate over `days` (NOT option PnL; headline key carries its universe). * view="positions" — the RECEIPTS: realized (closed) paper trades from the engine's own daily pick, row-level, cohort-filtered (`policy_version`, default live). Over `days`, `limit`. * view="performance" — cohort AGGREGATE of the receipts over `days` (win rate, avg/median/best/worst), `direction`, `min_premium_score`, `policy_version`. When the cohort has no closed trades, every aggregate is `null` and `total_trades` is 0 — NEVER 0.0. A `null` here means "not measured yet", not "zero percent"; do not render it as a result. All returns are FRACTIONS (0.40 = +40%). Realized data serves closed windows only. Paper-traded research data; not investment advice. Args: view: which surface (see above). Default "labels". horizon: "same_day" | "3d" (labels/summary/exit_rule). If omitted, the native default per view is used: labels/summary => "same_day" (the live GIGO policy), exit_rule => "3d" (its excursion window). group_by: summary grouping dimension. scan_date / scan_date_from / scan_date_to: date filters (per view). ticker / direction / delta_min / delta_max / min_overnight_score / exit_reason / outcome: row/aggregate filters (per view). days: lookback window (surface/win_rate/positions/performance). limit: max rows (labels 1-200, signal_performance 1-50, positions 1-200). aggregate_only: labels/surface views — summary stats instead of rows. On `surface` this is also the only mode immune to the 200-row cap. include_open: surface view — include not-yet-closed windows. targets / stops: harvest view — PERCENT grids. target_pct / stop_pct / rule / trail_pct / activation_pct: exit_rule view. policy_version: positions/performance cohort filter. The live default is the PAIR (policy label + cohort start date) — the label alone does not define the cohort, since disowned cohorts remain in the ledger under the same label. Responses carry `cohort_start`; a zero row_count under the live cohort means it has not accrued closed trades yet, not that there is no track record, and the aggregates come back `null` rather than 0.0. Pass "all" for every era, but note that "all" returns cohorts the engine has REPUDIATED — not merely older exit mechanics — so it is not a track record and must not be aggregated into one. Read the response `note` before quoting any number from it. min_premium_score: performance view floor.

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• post_lint_javascript

  webbersites-x402-data-api

  JavaScript / Node lint: POST {code}, get the bugs back with line numbers. Syntax errors come from the real V8 parser (compile-only — code is never executed), plus deterministic checks: loose == coercion, assignment in conditions, comparisons with NaN, const reassignment (runtime TypeError), var pitfalls, unused variables, leftover console.log. Handles ESM imports, template literals, regex. No AI. Max 128 KB. ($0.002 per call, paid via x402)

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• get_contact_summary

  savi-tools

  Rolodex overview: how many contacts the subscriber has, how many have a phone or email, and the top industries and tags. Answers "how many contacts do I have?" and "what industries are my contacts in?" Use get_contact_history to look up specific people.

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